Package com.irurueta.geometry.estimators

Class EuclideanTransformation2DRobustEstimator

java.lang.Object
com.irurueta.geometry.estimators.EuclideanTransformation2DRobustEstimator
Direct Known Subclasses:
LMedSEuclideanTransformation2DRobustEstimator, MSACEuclideanTransformation2DRobustEstimator, PROMedSEuclideanTransformation2DRobustEstimator, PROSACEuclideanTransformation2DRobustEstimator, RANSACEuclideanTransformation2DRobustEstimator
public abstract class EuclideanTransformation2DRobustEstimator extends Object
This is an abstract class to robustly find the best Euclidean transformation for collections of matching 2D points. Implementations of this class should be able to detect and discard outliers in order to find the best solution.

  • Field Details

    • MINIMUM_SIZE

      public static final int MINIMUM_SIZE
      Minimum number of matched points required to estimate an Euclidean 2D transformation.
      See Also:

    • WEAK_MINIMUM_SIZE

      public static final int WEAK_MINIMUM_SIZE
      For some point configurations a solution can be found with only 2 points.
      See Also:

    • DEFAULT_PROGRESS_DELTA

      public static final float DEFAULT_PROGRESS_DELTA
      Default amount of progress variation before notifying a change in estimation progress. By default, this is set to 5%.
      See Also:

    • MIN_PROGRESS_DELTA

      public static final float MIN_PROGRESS_DELTA
      Minimum allowed value for progress delta.
      See Also:

    • MAX_PROGRESS_DELTA

      public static final float MAX_PROGRESS_DELTA
      Maximum allowed value for progress delta.
      See Also:

    • DEFAULT_CONFIDENCE

      public static final double DEFAULT_CONFIDENCE
      Constant defining default confidence of the estimated result, which is 99%. This means that with a probability of 99% estimation will be accurate because chosen sub-samples will be inliers.
      See Also:

    • DEFAULT_MAX_ITERATIONS

      public static final int DEFAULT_MAX_ITERATIONS
      Default maximum allowed number of iterations.
      See Also:

    • MIN_CONFIDENCE

      public static final double MIN_CONFIDENCE
      Minimum allowed confidence value.
      See Also:

    • MAX_CONFIDENCE

      public static final double MAX_CONFIDENCE
      Maximum allowed confidence value.
      See Also:

    • MIN_ITERATIONS

      public static final int MIN_ITERATIONS
      Minimum allowed number of iterations.
      See Also:

    • DEFAULT_REFINE_RESULT

      public static final boolean DEFAULT_REFINE_RESULT
      Indicates that is refined by default using Levenberg-Marquardt fitting algorithm over found inliers.
      See Also:

    • DEFAULT_KEEP_COVARIANCE

      public static final boolean DEFAULT_KEEP_COVARIANCE
      Indicates that covariance is not kept by default after refining result.
      See Also:

    • DEFAULT_ROBUST_METHOD

      public static final com.irurueta.numerical.robust.RobustEstimatorMethod DEFAULT_ROBUST_METHOD
      Default robust estimator method when none is provided.

    • listener

      protected EuclideanTransformation2DRobustEstimatorListener listener
      Listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

    • locked

      protected boolean locked
      Indicates if this estimator is locked because an estimation is being computed.

    • progressDelta

      protected float progressDelta
      Amount of progress variation before notifying a progress change during estimation.

    • confidence

      protected double confidence
      Amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%). The amount of confidence indicates the probability that the estimated result is correct. Usually this value will be close to 1.0, but not exactly 1.0.

    • maxIterations

      protected int maxIterations
      Maximum allowed number of iterations. When the maximum number of iterations is exceeded, result will not be available, however an approximate result will be available for retrieval.

    • inliersData

      protected com.irurueta.numerical.robust.InliersData inliersData
      Data related to inliers found after estimation.

    • refineResult

      protected boolean refineResult
      Indicates whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers. If true, inliers will be computed and kept in any implementation regardless of the settings.

    • keepCovariance

      private boolean keepCovariance
      Indicates whether covariance must be kept after refining result. This setting is only taken into account if result is refined.

    • covariance

      private com.irurueta.algebra.Matrix covariance
      Estimated covariance of estimated 2D Euclidean transformation. This is only available when result has been refined and covariance is kept.

    • inputPoints

      protected List<Point2D> inputPoints
      List of points to be used to estimate an Euclidean 2D transformation. Each point in the list of input points must be matched with the corresponding point in the list of output points located at the same position. Hence, both input points and output points must have the same size, and their size must be greater or equal than MINIMUM_SIZE.

    • outputPoints

      protected List<Point2D> outputPoints
      List of points to be used to estimate an Euclidean 2D transformation. Each point in the lis tof output points must be matched with the corresponding point in the list of input points located at the same position. Hence, both input points and output points must have the same size, and their size must be greater or equal than MINIMUM_SIZE.

    • weakMinimumSizeAllowed

      private boolean weakMinimumSizeAllowed
      Indicates whether estimation can start with only 2 points or not. True allows 2 points, false requires 3.

  • Constructor Details

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator()
      Constructor.

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator(List<Point2D> inputPoints, List<Point2D> outputPoints)
      Constructor with lists of points to be used to estimate an Euclidean 2D transformation. Points in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints)
      Constructor with listener and lists of points to be used to estimate an Euclidean 2D transformation. Points in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator(boolean weakMinimumSizeAllowed)
      Constructor.
      Parameters:
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, boolean weakMinimumSizeAllowed)
      Constructor.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator(List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed)
      Constructor with lists of points to be used to estimate an Euclidean 2D transformation. Points in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • EuclideanTransformation2DRobustEstimator

      protected EuclideanTransformation2DRobustEstimator(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed)
      Constructor with listener and lists of points to be used to estimate an Euclidean 2D transformation. Points in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

  • Method Details

    • getInputPoints

      public List<Point2D> getInputPoints()
      Returns list of input points to be used to estimate an Euclidean 2D transformation. Each point in the list of input points must be matched with the corresponding point in the list of output points located at the same position. Hence, both input points and output points must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Returns:
      list of input points to be used to estimate an Euclidean 2D transformation.

    • getOutputPoints

      public List<Point2D> getOutputPoints()
      Returns list of output points to be used to estimate an Euclidean 2D transformation. Each point in the list of output points must be matched with the corresponding point in the list of input points located at the same position. Hence, both input points and output points must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Returns:
      list of output points to be used to estimate an Euclidean 2D transformation.

    • setPoints

      public void setPoints(List<Point2D> inputPoints, List<Point2D> outputPoints) throws LockedException
      Sets list of points to be used to estimate an Euclidean 2D transformation. Points in the list located at the same position are considered to be matched. Hence, both lists must have the same size, and their size must be greater or equal than MINIMUM_SIZE.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.
      LockedException - if estimator is locked because a computation is already in progress.

    • isReady

      public boolean isReady()
      Indicates if estimator is ready to start the Euclidean 2D transformation estimation. This is true when input data (i.e. lists of matched points) are provided and a minimum of MINIMUM_SIZE points are available.
      Returns:
      true if estimator is ready, false otherwise.

    • getQualityScores

      public double[] getQualityScores()
      Returns quality scores corresponding to each pair of matched points. The larger the score value the better the quality of the matching. This implementation always returns null. Subclasses using quality scores must implement proper behaviour.
      Returns:
      quality scores corresponding to each pair of matched points.

    • setQualityScores

      public void setQualityScores(double[] qualityScores) throws LockedException
      Sets quality scores corresponding to each pair of matched points. The larger the score value the better the quality of the matching. This implementation makes no action. Subclasses using quality scores must implement proper behaviour.
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      Throws:
      LockedException - if robust estimator is locked because an estimation is already in progress.
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 samples).

    • getListener

      public EuclideanTransformation2DRobustEstimatorListener getListener()
      Returns reference to listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      Returns:
      listener to be notified of events.

    • setListener

      public void setListener(EuclideanTransformation2DRobustEstimatorListener listener) throws LockedException
      Sets listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      Parameters:
      listener - listener to be notified of events.
      Throws:
      LockedException - if robust estimator is locked.

    • isListenerAvailable

      public boolean isListenerAvailable()
      Indicates whether listener has been provided and is available for retrieval.
      Returns:
      true if available, false otherwise.

    • isWeakMinimumSizeAllowed

      public boolean isWeakMinimumSizeAllowed()
      Indicates whether estimation can start with only 2 points or not.
      Returns:
      true allows 2 points, false requires 3.

    • setWeakMinimumSizeAllowed

      public void setWeakMinimumSizeAllowed(boolean weakMinimumSizeAllowed) throws LockedException
      Specifies whether estimation can start with only 2 points or not.
      Parameters:
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Throws:
      LockedException - if estimator is locked.

    • getMinimumPoints

      public int getMinimumPoints()
      Required minimum number of point correspondences to start the estimation. Can be either 2 or 3.
      Returns:
      minimum number of point correspondences.

    • isLocked

      public boolean isLocked()
      Indicates if this instance is locked because estimation is being computed.
      Returns:
      true if locked, false otherwise.

    • getProgressDelta

      public float getProgressDelta()
      Returns amount of progress variation before notifying a progress change during estimation.
      Returns:
      amount of progress variation before notifying a progress change during estimation.

    • setProgressDelta

      public void setProgressDelta(float progressDelta) throws LockedException
      Sets amount of progress variation before notifying a progress change during estimation.
      Parameters:
      progressDelta - amount of progress variation before notifying a progress change during estimation.
      Throws:
      IllegalArgumentException - if progress delta is less than zero or greater than 1.
      LockedException - if this estimator is locked because an estimation is being computed.

    • getConfidence

      public double getConfidence()
      Returns amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%). The amount of confidence indicates the probability that the estimated result is correct. Usually this value will be close to 1.0, but not exactly 1.0.
      Returns:
      amount of confidence as a value between 0.0 and 1.0.

    • setConfidence

      public void setConfidence(double confidence) throws LockedException
      Sets amount of confidence expressed as a value between 0.0 and 1.0 (which is equivalent to 100%). The amount of confidence indicates the probability that the estimated result is correct. Usually this value will be close to 1.0, but not exactly 1.0.
      Parameters:
      confidence - confidence to be set as a value between 0.0 and 1.0.
      Throws:
      IllegalArgumentException - if provided value is not between 0.0 and 1.0.
      LockedException - if this estimator is locked because an estimator is being computed.

    • getMaxIterations

      public int getMaxIterations()
      Returns maximum allowed number of iterations. If maximum allowed number of iterations is achieved without converging to a result when calling estimate(), a RobustEstimatorException will be raised.
      Returns:
      maximum allowed number of iterations.

    • setMaxIterations

      public void setMaxIterations(int maxIterations) throws LockedException
      Sets maximum allowed number of iterations. When the maximum number of iterations is exceeded, result will not be available, however an approximate result will be available for retrieval.
      Parameters:
      maxIterations - maximum allowed number of iterations to be set.
      Throws:
      IllegalArgumentException - if provided value is less than 1.
      LockedException - if this estimator is locked because an estimation is being computed.

    • getInliersData

      public com.irurueta.numerical.robust.InliersData getInliersData()
      Gets data related to inliers found after estimation.
      Returns:
      data related to inliers found after estimation.

    • isResultRefined

      public boolean isResultRefined()
      Indicates whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers. If ture, inliers will be computed and kept in any implementation regardless of the settings.
      Returns:
      true to refine result, false to simply use result found by robust estimator without further refining.

    • setResultRefined

      public void setResultRefined(boolean refineResult) throws LockedException
      Specifies whether result must be refined using Levenberg-Marquardt fitting algorithm over found inliers.
      Parameters:
      refineResult - true to refine result, false to simply use result found by robust estimator without further refining.
      Throws:
      LockedException - if estimator is locked.

    • isCovarianceKept

      public boolean isCovarianceKept()
      Indicates whether covariance must be kept after refining result. This setting is only taken into account if result is refined.
      Returns:
      true if covariance must be kept after refining result, false otherwise.

    • setCovarianceKept

      public void setCovarianceKept(boolean keepCovariance) throws LockedException
      Specifies whether covariance must be kept after refining result. This setting is only taken into account if result is refined.
      Parameters:
      keepCovariance - true if covariance must be kept after refining result, false otherwise.
      Throws:
      LockedException - if estimator is locked.

    • getCovariance

      public com.irurueta.algebra.Matrix getCovariance()
      Gets estimated covariance of estimated 3D point if available. This is only available when result has been refined and covariance is kept.
      Returns:
      estimated covariance or null.

    • estimate

      public abstract EuclideanTransformation2D estimate() throws LockedException, NotReadyException, com.irurueta.numerical.robust.RobustEstimatorException
      Estimates an Euclidean 2D transformation using a robust estimator and the best set of matched 2D point correspondences found using the robust estimator.
      Returns:
      an Euclidean 2D transformation.
      Throws:
      LockedException - if robust estimator is locked because an estimation is already in progress.
      NotReadyException - if provided input data is not enough to start the estimation.
      com.irurueta.numerical.robust.RobustEstimatorException - if estimation fails for any reason (i.e. numerical instability, no solution available, etc).

    • getMethod

      public abstract com.irurueta.numerical.robust.RobustEstimatorMethod getMethod()
      Returns method being used for robust estimation.
      Returns:
      method being used for robust estimation.

    • create

      public static EuclideanTransformation2DRobustEstimator create(com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 matched points).

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points or scores don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      qualityScores - quality scores corresponding to each pair of matched points.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided quality scores don't have the required minimum size.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size of their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(double[] qualityScores, boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided quality scores length is smaller than MINIMUM_SIZE (i.e. 3 matched points).

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points or scores don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, double[] qualityScores, boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided quality scores don't have the required minimum size.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, boolean weakMinimumSizeAllowed, com.irurueta.numerical.robust.RobustEstimatorMethod method)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using provided robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      method - method of a robust estimator algorithm to estimate the best Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size of their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create()
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size of their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(double[] qualityScores)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points ot be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of points.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, double[] qualityScores)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      qualityScores - quality scores corresponding to each pair of matched points.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points ot be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size of their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(double[] qualityScores, boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points ot be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, double[] qualityScores, boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.

    • create

      public static EuclideanTransformation2DRobustEstimator create(EuclideanTransformation2DRobustEstimatorListener listener, List<Point2D> inputPoints, List<Point2D> outputPoints, double[] qualityScores, boolean weakMinimumSizeAllowed)
      Creates an Euclidean 2D transformation estimator based on 2D point correspondences and using default robust estimator method.
      Parameters:
      listener - listener to be notified of events such as when estimation starts, ends or its progress significantly changes.
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points ot be used to estimate an Euclidean 2D transformation.
      qualityScores - quality scores corresponding to each pair of matched points.
      weakMinimumSizeAllowed - true allows 2 points, false requires 3.
      Returns:
      an instance of Euclidean 2D transformation estimator.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • internalSetPoints

      private void internalSetPoints(List<Point2D> inputPoints, List<Point2D> outputPoints)
      Internal method to set lists of points to be used to estimate an Euclidean 2D transformation. This method does not check whether estimator is locked or not.
      Parameters:
      inputPoints - list of input points to be used to estimate an Euclidean 2D transformation.
      outputPoints - list of output points to be used to estimate an Euclidean 2D transformation.
      Throws:
      IllegalArgumentException - if provided lists of points don't have the same size or their size is smaller than MINIMUM_SIZE.

    • attemptRefine

      protected EuclideanTransformation2D attemptRefine(EuclideanTransformation2D transformation)
      Attempts to refine provided solution if refinement is requested. This method returns a refined solution of the same provided solution if refinement is not requested or has failed. If refinement is enabled, and it is requested to keep covariance, this method will also keep covariance of refined transformation.
      Parameters:
      transformation - transformation estimated by a robust estimator without refinement.
      Returns:
      solution after refinement (if requested) or the provided non-refined solution if not requested or refinement failed.

    • getRefinementStandardDeviation

      protected abstract double getRefinementStandardDeviation()
      Gets standard deviation used for Levenberg-Marquardt fitting during refinement. Returned value gives an indication of how much variance each residual has. Typically, this value is related to the threshold used on each robust estimation, since residuals of found inliers are within the range of such threshold.
      Returns:
      standard deviation used for refinement.